COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data
COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data
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DOI：
10.2196/19458
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发表时间：
2020-05-06
影响因子：
7.4
通讯作者：
Lopez Segui, Francesc
中科院分区：
文献类型：
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作者：
Ahmed, Wasim;Vidal-Alaball, Josep;Lopez Segui, Francesc
背景：自2019年12月初以来，冠状病毒病(新冠肺炎)在全球迅速传播，导致网络平台讨论增加。这些对话还包括社交媒体用户分享的各种阴谋。其中，一种流行的理论将5G与新冠肺炎的传播联系在一起，导致错误信息和英国5G塔楼被烧毁。了解虚假新闻的驱动因素和旨在隔离和回扣虚假信息的快速政策是打击虚假新闻的关键。目的：本研究的目的是了解5G新冠肺炎阴谋论的驱动因素和处理此类虚假信息的策略。方法：对英国推特上流行#5G冠状病毒标签的7天内(2020年3月27日星期五至2020年4月4日星期六)推特上的数据进行社交网络分析和内容分析。通过社交网络图聚类分析有影响力的用户。节点的大小根据节点的介数中心度进行排序，并使用Clauset-Newman-Moore算法按簇对图的顶点进行分组。结果：社会网络分析发现，最大的两个网络结构由隔离组和广播组组成。分析还显示，缺乏一位积极打击此类虚假信息的权威人士。内容分析显示，在233条样本推文中，34.8%(n=81)包含5G与新冠肺炎相关的观点，32.2%(n=75)谴责阴谋论，33.0%(n=77)是一般推文，没有表达任何个人观点或观点。因此，65.2%(n=152)的推文来自非阴谋论支持者，这表明，尽管该话题吸引了大量用户，但只有少数用户真正相信了阴谋论。这份报告还显示，假新闻网站是用户分享的最受欢迎的网络来源；尽管如此，YouTube视频也被分享。该研究还确定了一个唯一目的是在Twitter上传播阴谋论的账户。结论：旨在使虚假信息来源合法化的快速和有针对性的干预相结合，是减少其影响的关键。那些表达反对阴谋论、链接诱饵或分享幽默推文的用户无意中提升了这个话题的知名度，表明政策制定者应该坚持努力孤立基于假新闻的观点。许多社交媒体平台为用户提供了举报不当内容的能力，这是应该使用的。这项研究是首次在推特上新冠肺炎的背景下分析5G阴谋论，为卫生当局在大流行背景下未来如何打击谣言提供实践指导。
Background: Since the beginning of December 2019, the coronavirus disease (COVID-19) has spread rapidly around the world, which has led to increased discussions across online platforms. These conversations have also included various conspiracies shared by social media users. Amongst them, a popular theory has linked 5G to the spread of COVID-19, leading to misinformation and the burning of 5G towers in the United Kingdom. The understanding of the drivers of fake news and quick policies oriented to isolate and rebate misinformation are keys to combating it.Objective: The aim of this study is to develop an understanding of the drivers of the 5G COVID-19 conspiracy theory and strategies to deal with such misinformation.Methods: This paper performs a social network analysis and content analysis of Twitter data from a 7-day period (Friday, March 27, 2020, to Saturday, April 4, 2020) in which the #5GCoronavirus hashtag was trending on Twitter in the United Kingdom. Influential users were analyzed through social network graph clusters. The size of the nodes were ranked by their betweenness centrality score, and the graph's vertices were grouped by cluster using the Clauset-Newman-Moore algorithm. The topics and web sources used were also examined.Results: Social network analysis identified that the two largest network structures consisted of an isolates group and a broadcast group. The analysis also revealed that there was a lack of an authority figure who was actively combating such misinformation. Content analysis revealed that, of 233 sample tweets, 34.8% (n=81) contained views that 5G and COVID-19 were linked, 32.2% (n=75) denounced the conspiracy theory, and 33.0% (n=77) were general tweets not expressing any personal views or opinions. Thus, 65.2% (n=152) of tweets derived from nonconspiracy theory supporters, which suggests that, although the topic attracted high volume, only a handful of users genuinely believed the conspiracy. This paper also shows that fake news websites were the most popular web source shared by users; although, YouTube videos were also shared. The study also identified an account whose sole aim was to spread the conspiracy theory on Twitter.Conclusions: The combination of quick and targeted interventions oriented to delegitimize the sources of fake information is key to reducing their impact. Those users voicing their views against the conspiracy theory, link baiting, or sharing humorous tweets inadvertently raised the profile of the topic, suggesting that policymakers should insist in the efforts of isolating opinions that are based on fake news. Many social media platforms provide users with the ability to report inappropriate content, which should be used. This study is the first to analyze the 5G conspiracy theory in the context of COVID-19 on Twitter offering practical guidance to health authorities in how, in the context of a pandemic, rumors may be combated in the future.